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      Surveillance to maintain the sensitivity of genotype-based antibiotic resistance diagnostics

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          Abstract

          The sensitivity of genotype-based diagnostics that predict antimicrobial susceptibility is limited by the extent to which they detect genes and alleles that lead to resistance. As novel resistance variants are expected to emerge, such sensitivity is expected to decline unless the new variants are detected and incorporated into the diagnostic. Here, we present a mathematical framework to define how many diagnostic failures may be expected under varying surveillance regimes and thus quantify the surveillance needed to maintain the sensitivity of genotype-based diagnostics.

          Abstract

          A simple mathematical framework that defines the rates of sampling and phenotypic testing necessary to efficiently detect novel resistance variants and thus maintain the sensitivity of genotype-based antimicrobial resistance diagnostics.

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          Most cited references15

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          Anthropological and socioeconomic factors contributing to global antimicrobial resistance: a univariate and multivariable analysis

          Understanding of the factors driving global antimicrobial resistance is limited. We analysed antimicrobial resistance and antibiotic consumption worldwide versus many potential contributing factors.
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            Rapid point of care diagnostic tests for viral and bacterial respiratory tract infections—needs, advances, and future prospects

            Summary Respiratory tract infections rank second as causes of adult and paediatric morbidity and mortality worldwide. Respiratory tract infections are caused by many different bacteria (including mycobacteria) and viruses, and rapid detection of pathogens in individual cases is crucial in achieving the best clinical management, public health surveillance, and control outcomes. Further challenges in improving management outcomes for respiratory tract infections exist: rapid identification of drug resistant pathogens; more widespread surveillance of infections, locally and internationally; and global responses to infections with pandemic potential. Developments in genome amplification have led to the discovery of several new respiratory pathogens, and sensitive PCR methods for the diagnostic work-up of these are available. Advances in technology have allowed for development of single and multiplexed PCR techniques that provide rapid detection of respiratory viruses in clinical specimens. Microarray-based multiplexing and nucleic-acid-based deep-sequencing methods allow simultaneous detection of pathogen nucleic acid and multiple antibiotic resistance, providing further hope in revolutionising rapid point of care respiratory tract infection diagnostics.
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              Developing an in silico minimum inhibitory concentration panel test for Klebsiella pneumoniae

              Antimicrobial resistant infections are a serious public health threat worldwide. Whole genome sequencing approaches to rapidly identify pathogens and predict antibiotic resistance phenotypes are becoming more feasible and may offer a way to reduce clinical test turnaround times compared to conventional culture-based methods, and in turn, improve patient outcomes. In this study, we use whole genome sequence data from 1668 clinical isolates of Klebsiella pneumoniae to develop a XGBoost-based machine learning model that accurately predicts minimum inhibitory concentrations (MICs) for 20 antibiotics. The overall accuracy of the model, within ±1 two-fold dilution factor, is 92%. Individual accuracies are ≥90% for 15/20 antibiotics. We show that the MICs predicted by the model correlate with known antimicrobial resistance genes. Importantly, the genome-wide approach described in this study offers a way to predict MICs for isolates without knowledge of the underlying gene content. This study shows that machine learning can be used to build a complete in silico MIC prediction panel for K. pneumoniae and provides a framework for building MIC prediction models for other pathogenic bacteria.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Biol
                PLoS Biol
                plos
                plosbiol
                PLoS Biology
                Public Library of Science (San Francisco, CA USA )
                1544-9173
                1545-7885
                12 November 2019
                November 2019
                12 November 2019
                : 17
                : 11
                : e3000547
                Affiliations
                [1 ] Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
                [2 ] Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
                [3 ] Division of Infectious Diseases, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
                University of Melbourne, AUSTRALIA
                Author notes

                The authors have declared that no competing interests exist.

                ‡ These authors are co-senior authors on this work.

                Author information
                http://orcid.org/0000-0003-1372-1301
                http://orcid.org/0000-0001-6000-8387
                http://orcid.org/0000-0003-1504-9213
                http://orcid.org/0000-0001-5646-1314
                Article
                PBIOLOGY-D-19-02225
                10.1371/journal.pbio.3000547
                6874359
                31714937
                c5596dc5-ff2e-4fc1-9f84-b4c6fac199dc
                © 2019 Hicks et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 31 July 2019
                : 29 October 2019
                Page count
                Figures: 2, Tables: 1, Pages: 10
                Funding
                Funded by: National Institute of General Medical Sciences (US)
                Award ID: U54GM088558
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: R01AI132606
                Award Recipient :
                This work was supported by Grant U54GM088558 (Models of Infectious Disease Agent Study, Center for Communicable Disease Dynamics) from the National Institute of General Medical Sciences (ML) and Grant R01AI132606 from the National Institute of Allergy and Infectious Diseases (ALH, SMK, YHG). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Short Reports
                Biology and Life Sciences
                Microbiology
                Microbial Control
                Antimicrobial Resistance
                Antibiotic Resistance
                Medicine and Health Sciences
                Pharmacology
                Antimicrobial Resistance
                Antibiotic Resistance
                Biology and Life Sciences
                Microbiology
                Microbial Control
                Antimicrobial Resistance
                Medicine and Health Sciences
                Pharmacology
                Antimicrobial Resistance
                Biology and Life Sciences
                Genetics
                Heredity
                Genetic Mapping
                Variant Genotypes
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Bacterial Pathogens
                Neisseria Gonorrhoeae
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
                Bacterial Pathogens
                Neisseria Gonorrhoeae
                Biology and Life Sciences
                Organisms
                Bacteria
                Neisseria
                Neisseria Gonorrhoeae
                Medicine and Health Sciences
                Pharmacology
                Drugs
                Antimicrobials
                Antibiotics
                Penicillin
                Biology and Life Sciences
                Microbiology
                Microbial Control
                Antimicrobials
                Antibiotics
                Penicillin
                Biology and life sciences
                Biochemistry
                Proteins
                DNA-binding proteins
                Medicine and Health Sciences
                Epidemiology
                Disease Surveillance
                Medicine and Health Sciences
                Pharmacology
                Drugs
                Antimicrobials
                Antibiotics
                Biology and Life Sciences
                Microbiology
                Microbial Control
                Antimicrobials
                Antibiotics
                Custom metadata
                vor-update-to-uncorrected-proof
                2019-11-22
                All data are publicly available in SRA/ENA (accession numbers provided in Table 1) or in referenced publications.

                Life sciences
                Life sciences

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